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Integrating data from multiple sources is essential in the age of big data, but it can be a challenging and time-consuming task. This handy cookbook provides dozens of ready-to-use recipes for using Apache Sqoop, the command-line interface application that optimizes data transfers between relational databases and Hadoop.
Sqoop is both powerful and bewildering, but with this cookbook’s problem-solution-discussion format, you’ll quickly learn how to deploy and then apply Sqoop in your environment. The authors provide MySQL, Oracle, and PostgreSQL database examples on GitHub that you can easily adapt for SQL Server, Netezza, Teradata, or other relational systems.
- Transfer data from a single database table into your Hadoop ecosystem
- Keep table data and Hadoop in sync by importing data incrementally
- Import data from more than one database table
- Customize transferred data by calling various database functions
- Export generated, processed, or backed-up data from Hadoop to your database
- Run Sqoop within Oozie, Hadoop’s specialized workflow scheduler
- Load data into Hadoop’s data warehouse (Hive) or database (HBase)
- Handle installation, connection, and syntax issues common to specific database vendors
- Sales Rank: #705577 in Books
- Published on: 2013-07-26
- Released on: 2013-07-23
- Original language: English
- Number of items: 1
- Dimensions: 9.19" h x .19" w x 7.00" l, .36 pounds
- Binding: Paperback
- 94 pages
Amazon.com Review
Q&A with Kathleen Ting and Jarek Jarcec Cecho, author of "Apache Sqoop Cookbook"
Q. What makes this book important right now?
A. Hadoop has quickly become the standard for processing and analyzing Big Data. In order to integrate a new Hadoop deployment into your existing environment, you will need to transfer data stored in relational databases into Hadoop. Sqoop optimizes data transfers between Hadoop and databases with a command line interface listing 60 parameters. In this book, we'll focus on applying the parameters in common use cases to help you deploy and use Sqoop in your environment.
Q. What do you hope that readers of your book will walk away with?
A. One recipe at a time, this book guides you from basic commands not requiring prior Sqoop knowledge all the way to very advanced use cases. These recipes are detailed enough not only to enable you to deploy them within your environment but also to understand Sqoop's inner workings.
Q. Can you give us a little taste of the contents?
A. Imagine a scenario where you are incrementally importing records from MySQL into Hadoop. When you resume importing and noticing that some records have been modified, you also want to include those updated records. How do you drop the older copies of records when records have been updated and then merge in the newer copies?
This sounds like a use-case for using the lastmodified incremental mode. Internally, the lastmodified import consists of two standalone MapReduce jobs. The first job will import the delta of changed data similarly to the way normal import does. This import job will save data in a temporary directory on HDFS. The second job will take both the old and new data and will merge them together into the final output, preserving only the last updated value for each row.
Here's an example:
sqoop import \
--connect jdbc:mysql://mysql.example.com/sqoop \
--username sqoop \
--password sqoop \
--table visits \
--incremental lastmodified \
--check-column last_update_date \
--last-value "2013-05-22 01:01:01"
About the Author
Kathleen Ting is currently a Customer Operations Engineering Manager at Cloudera where she helps customers deploy and use the Hadoop ecosystem in production. She has spoken on Hadoop, ZooKeeper, and Sqoop at many Big Data conferences including Hadoop World, ApacheCon, and OSCON. She's contributed to several projects in the open source community and is a Committer and PMC Member on Sqoop.
Jarek Jarcec Cecho is currently a Software Engineer at Cloudera where he develops software to help customers better access and integrate with the Hadoop ecosystem. He has led the Sqoop community in the architecture of the next generation of Sqoop, known as Sqoop 2. He's contributed to several projects in the open source community and is a Committer and PMC Member on Sqoop, Flume, and MRUnit.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Excellent practical hands-on examples to get started with Sqoop right away
By Todd Nemet
Disclosure: I know Kathleen because we worked together fairly closely at Cloudera for a year or so.
Disclosure: Further, through the use of my extremely good looks and Midwestern charm, I wheedled a free copy of this book from Kathleen when I bumped into her earlier this week. She didn't have a chance.
This book is an excellent quick introduction for getting quickly up and running with Sqoop. There is a cursory section on installing it and grabbing the jdbc driver(s) then it's all about the vagaries of moving data back and forth between HDFS and your RDBMS.
Personally I like the structure of the book. Each "recipe" in the cookbook states a problem, then states the solution (with a working example), then there is a brief discussion explaining why and how this solution works. Most of these sections build on the previous examples.
So by reading it in order you get a very logical and step-by-step understanding of how Sqoop works along with at least one working example for each step. You could work through the examples on your laptop (code is on Github) as you go through the book for a deeper understanding.
It is also possible to use this book by finding your problem in the table of contents and flipping right to that section.
Other people may have different styles of learning, so for them there is the documentation on the Apache site or the section in Hadoop: The Definitive Guide on Sqoop. But with the Hadoop ecosystem I find that so much of getting it to work is trial and error, so having practical working examples is worth the price of the book.
1 of 2 people found the following review helpful.
Updated for Sqoop2?
By Chia-heng Yao
TOC looks good. However, the main question now is whether this book is updated for Sqoop2 - a major architectural re-design. For starter, client-side installation is eliminated. Connectors are also moved away from the JDBC paradigm. Given that the author is an insider, and Sqoop2 was well near GA in 2012 (the author herself blogged about it in Jan, 2012 - https://blogs.apache.org/sqoop/entry/apache_sqoop_highlights_of_sqoop), one would expect so. However, the book blurb and extracts give no indication at all.
If the book is Sqoop2-compliant, I will buy it. If not, then not. Not knowing this, I can only give 3 stars as a compromise.
1 of 1 people found the following review helpful.
Very very damn useful
By Christian
This book was very helpful when I needed to import data from MySQL into a S3-backed Hive data warehouse using an Oozie workflow, lots of the little recipes helped to get my job done way quicker than I would've imagined. I definitely recommend anyone interested in bulk loading data from a relational database into the Hadoop world to get this book.
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